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Run Deep Learning Jobs on Kubernetes in An Easy Way. (This project will be transferred to Kubeflow organization)

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Arena

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Overview

Arena is a command-line interface for the data scientists to run and monitor the machine learning training jobs and check their results in an easy way. Currently it supports solo/distributed TensorFlow training. In the backend, it is based on Kubernetes, helm and Kubeflow. But the data scientists can have very little knowledge about kubernetes.

Meanwhile, the end users require GPU resource and node management. Arena also provides top command to check available GPU resources in the Kubernetes cluster.

In one word, Arena's goal is to make the data scientists feel like to work on a single machine but with the Power of GPU clusters indeed.

For the Chinese version, please refer to 中文文档

Setup

You can follow up the Installation guide

User Guide

Arena is a command-line interface to run and monitor the machine learning training jobs and check their results in an easy way. Currently it supports solo/distributed training.

Demo

Developing

Prerequisites:

  • Go >= 1.8
mkdir -p $(go env GOPATH)/src/github.com/kubeflow
cd $(go env GOPATH)/src/github.com/kubeflow
git clone https://github.com/kubeflow/arena.git
cd arena
make

arena binary is located in directory arena/bin. You may want to add the directory to $PATH.

Then you can follow Installation guide for developer

CPU Profiling

# set profile rate (HZ)
export PROFILE_RATE=1000

# arena {command} --pprof
arena list --pprof
INFO[0000] Dump cpu profile file into /tmp/cpu_profile

Then you can analyze the profile by following Go CPU profiling: pprof and speedscope

FAQ

Please refer to FAQ

CLI Document

Please refer to arena.md

RoadMap

See RoadMap

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Run Deep Learning Jobs on Kubernetes in An Easy Way. (This project will be transferred to Kubeflow organization)

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License

Apache-2.0, Unknown licenses found

Licenses found

Apache-2.0
LICENSE
Unknown
license.txt

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